Near‐Infrared Annihilation of Conductive Filaments in Quasiplane MoSe₂/Bi₂Se₃ Nanosheets for Mimicking Heterosynaptic Plasticity

Abstract

The inherent limitations of traditional silicon technology in the implementation of machine learning could be addressed by neuromorphic computing since it is able to mimic the resilience, versatility, and efficiency of the human brain. [1][2][3][4] Synaptic It is desirable to imitate synaptic functionality to break through the memory wall in traditional von Neumann architecture. Modulating heterosynaptic plasticity between pre-and postneurons by another modulatory interneuron ensures the computing system to display more complicated functions. Optoelectronic devices facilitate the inspiration for high-performance artificial heterosynaptic systems. Nevertheless, the utilization of near-infrared (NIR) irradiation to act as a modulatory terminal for heterosynaptic plasticity emulation has not yet been realized. Here, an NIR resistive random access memory (RRAM) is reported, based on quasiplane MoSe 2 /Bi 2 Se 3 heterostructure in which the anomalous NIR threshold switching and NIR reset operation are realized. Furthermore, it is shown that such an NIR irradiation can be employed as a modulatory terminal to emulate heterosynaptic plasticity. The reconfigurable 2D image recognition is also demonstrated by an RRAM crossbar array. NIR annihilation effect in quasiplane MoSe 2 /Bi 2 Se 3

Van der Waals Epitaxy of Horizontally Orientated Bismuth Iodide/Silicon Heterostructure for Nonvolatile Resistive‐Switching Memory with Multistate Data Storage

“…Compared with traditional synaptic devices, they are more energy‐efficient and highly scalable. [ 6–13 ] Accordingly, RRAMs have a considerable potential in artificial neurocomputing networks, which have efficient processing and self‐learning capacities and are anticipated to replace the traditional Boolean computing paradigm in the future.…”

MXene Quantum Dot/Polymer Hybrid Structures with Tunable Electrical Conductance and Resistive Switching for Nonvolatile Memory Devices

“…An effective strategy to realize resistive switching for memory effect is organic‐inorganic hybrid design in polymer device, with the merits of tailorable components, tunable properties, solution process and low‐cost manufacturing . In the organic–inorganic hybrid systems, insulating or semiconducting polymers are widely used as active matrix, low dimensional inorganic materials including zero dimensional (0D) nanodots, 1D nanotubes and 2D nanosheets are introduced into polymer matrix as charge trapping to trigger the resistive switching. Among these nanomaterials, quantum dots (QDs) have attracted much attention because of outstanding quantum confinement for charge trapping and well dispersion in matrix for high reproducibility as well as operation stability.…”

2D Material Based Synaptic Devices for Neuromorphic Computing

“…2D materials, due to their atomically thin structure and intriguing physical properties which are sensitive to external stimuli, have proven to be good candidates for mimicking synaptic functions. They have advantages in various aspects, such as ultra‐low switching energies approaching femto joules, [ 37,51,56 ] spatially uniform switching, [ 38,44,56,97,211 ] perceptional capability with integrated memories and sensors, [ 70,73 ] heterosynaptic plasticity, [ 63–64,174,235,256 ] as well as mimicking multiterminal synaptic networks, [ 16,67,172,240 ] which are highly desirable for neuromorphic system. Nevertheless, 2D synaptic device based neuromorphic applications are still in the early stage.…”